Fivetran vs Matillion ETL
Detailed side-by-side comparison to help you choose the right tool
Fivetran
Automation & Workflows
Fivetran is an automated data movement platform that syncs data from applications, databases, and files into cloud destinations. It helps teams centralize reliable data for analytics, AI, and operational workflows.
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CustomMatillion ETL
Data Integration
Matillion ETL is cloud-based ETL software for data integration. It helps teams transform and move data across cloud data platforms.
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💡 Our Take
Choose Matillion ETL if your team needs visual transformation design, cloud ELT workflows, and reverse ETL in addition to loading data. Choose Fivetran if your priority is managed connector-based ingestion with less emphasis on designing transformations inside the ETL tool.
Fivetran - Pros & Cons
Pros
- ✓Largest connector library in the ELT space with 700+ pre-built sources and 900+ total integrations
- ✓Fully managed pipelines automatically handle schema changes, API updates, and source-side breakage without engineering intervention
- ✓Enterprise-grade security and compliance certifications (SOC 2 Type II, HIPAA, GDPR, ISO 27001) make it suitable for regulated industries like healthcare and finance
- ✓Strong SAP and ERP replication capabilities, including high-volume database CDC, used by enterprises like Coca-Cola for ~35,000 users
- ✓Free tier available with no credit card required, letting teams validate fit before committing
- ✓Hybrid deployment option keeps sensitive data within customer infrastructure while still benefiting from managed orchestration
Cons
- ✗Consumption-based MAR (Monthly Active Rows) pricing can scale unpredictably and become expensive for high-volume sources
- ✗Limited transformation flexibility compared to dedicated tools — relies on dbt-style SQL in the destination rather than in-pipeline logic
- ✗Less customizable than open-source alternatives like Airbyte, with custom connector work requiring the Connector SDK
- ✗Initial sync times for large databases can be slow and resource-intensive on the source system
- ✗Some niche or newer SaaS tools still require custom connector builds despite the large library
Matillion ETL - Pros & Cons
Pros
- ✓Supports both low-code and high-code ETL workflows, which helps mixed data teams collaborate instead of forcing every transformation into code.
- ✓Designed for cloud data platforms, with Matillion describing transformations performed directly within the customer’s data platform using ELT methodology.
- ✓Strong connector positioning: the website says teams can connect to virtually any data source, use pre-built connectors, create custom connectors in minutes, and download customer-created connectors from the Community.
- ✓Includes reverse ETL, so prepared data can be pushed back to business users and operational systems rather than only consumed in BI dashboards.
- ✓Customer results on the website include reducing long-running jobs from more than 22 hours to 6 hours and getting an entire infrastructure running in Matillion in 2 days.
- ✓The visual ELT designer is useful for building intricate transformations and analytics-ready datasets without relying only on handwritten pipeline code.
Cons
- ✗Pricing is usage-based and partly quote-dependent, so buyers still need Matillion or marketplace confirmation to model total annual cost, discounts, and overages.
- ✗The product is positioned around cloud data platforms, which may make it less suitable for teams that still need primarily on-premise ETL workflows.
- ✗The website emphasizes enterprise productivity and cloud architecture, so very small teams may find it more platform than they need for simple data sync tasks.
- ✗Because Matillion supports both low-code and high-code patterns, teams still need governance around naming, testing, orchestration, and ownership to avoid inconsistent pipeline design.
- ✗The page describes an extensive connector ecosystem but does not provide an exact connector count in the supplied content.
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